Multi-objective optimization of vehicle ride dynamic behaviors

A human-seat-suspension model with seven degrees-of-freedom was built on a 1/4 car model. The vertical acceleration, suspension work space and dynamic tire load were selected as the objective functions, and parameters of the suspension and seat cushion were selected as the design variables according to the results of parameter sensitivity analysis. Dimensionless method was introduced to make the optimization computation independent of the working conditions. Then a multi-objective optimization model was built to optimize the ride dynamic behavior of vehicle. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was employed for optimization computation and Pareto optimal set and Pareto frontier were obtained. Results show that seat cushion with small stiffness and large damping contributes to improve ride comfort without worsening other behaviors. In Pareto optimal set, the suspension stiffness is linearly directly proportional to suspension damping, which decides that optimal ride comfort and suspension work space can not be obtained simultaneously. Tire stiffness can be approximately determined based on dynamic tire load.